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companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We
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the application Skilled in either computational modelling or experimentation, paired with the willingness to work on both Personal characteristics To complete a doctoral degree (PhD), it is important that you are
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) to train shared models without centralising raw data. In practice, however, individual platforms operate under diverse environmental conditions, sensor calibrations, and system configurations
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include theoretical results, mathematical proofs, and computational algorithms, as well as open-source software and validation through simulations and analysis. Experimental demonstration is an option if it
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resistance of ceramic shell moulds used in investment casting. Advanced in situ experiments combined with multi-scale Finite Element Method (FEM) modelling will be employed to identify the key stress and
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University of Girona (UdG) - Institute of Computational Chemistry and Catalysis (IQCC) | Spain | 2 months ago
next-generation computational approaches to understand, predict, and engineer highly reactive intermediates in enzymatic catalysis. By combining quantum chemistry, molecular dynamics simulations, machine
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for the position. Preferred selection criteria Solid understanding of control theory, including classical and modern control design methods Experience with modelling and simulation of dynamic systems Programming
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methods, and governance models capable of identifying where power is concentrated and how it might be reconfigured to preserve organizational autonomy and national digital sovereignty. While principles
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to investigate electromagnetic wave propagation in time-varying THz waveguides. Job description Develop numerical simulation frameworks for time-varying electromagnetic systems, modeling ultrafast refractive-index
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federated learning and multimodal deep learning models for healthcare. The project will focus on enabling privacy-preserving learning from distributed healthcare data sources, including longitudinal medical